1. Field of the Invention
The present invention relates generally to processes for semiconductor manufacturing and more particularly to characterizing and monitoring the intra-field distortions of scanning projection systems used in ULSI photolithography.
2. Description of the Related Art
Today's lithographic processing requires ever tighter layer-to-layer overlay tolerances to meet device performance requirements. Overlay registration on critical layers can directly impact device performance, yield and repeatability. Typical microelectronic devices or circuits may have as many as 20 or more levels or pattern layers. The placement of patterned features on one level must match the placement of corresponding features on other levels—that is, they must overlap—within an accuracy which is some fraction of the minimum feature size or critical dimension (CD).
Overlay error is typically, although not exclusively, measured with a metrology tool appropriately called an overlay tool using several techniques. See Semiconductor Pattern Overlay, N. Sullivan, SPIE Critical Reviews Vol. CR52, 160:188. The term overlay metrology tool or overlay tool means any tool capable of determining the relative position of two alignment attributes that are separated within about 2000 um (microns) of each other. The importance of overlay error, and its impact on yield, have been extensively studied and documented. See Measuring Fab Overlay Programs, R. Martin et al., SPIE Conference on Metrology, Inspection, and Process Control for Microlithography XIII, 64:71, March 1999; A New Approach to Correlating Overlay and Yield, M. Preil et al., SPIE Conference on Metrology, Inspection, and Process Control for Microlithography XIII, 208:216, March 1999.
Lithographers have created statistical computer algorithms (for example, Klass II (See Lens Matching and Distortion Testing in a Multi-Stepper, Sub-Micron Environment, A. Yost et al., SPIE Vol. 1087, 233:244, 1989) and Monolith (See A Computer Aided Engineering Workstation for Registration Control, E. McFadden et al., SPIE Vol. 1087, 255:266, 1989)) that attempt to quantify and divide overlay error into repeatable or systematic and non-repeatable or random effects. See Matching of Multiple Wafer Steppers for 0.35 Micron Lithography Using Advanced Optimization Schemes, M. van den Brink et al., SPIE Vol. 1926, 188:207, 1993; A Computer Aided Engineering Workstation for Registration Control, supra; Semiconductor Pattern Overlay, supra; Machine Models and Registration, T. Zavecz, SPIE Critical Reviews Vol. CR52, 134:159. An overall theoretical review of overlay modeling can be found in the literature. See Semiconductor Pattern Overlay, supra.
Overlay error is typically divided into the following two major categories. The first category, inter-field or grid overlay error, is concerned with the actual position of the translation and rotation or yaw of the image field as recorded in the photoresist on a silicon wafer using an exposure tool, i.e., stepper or scanner. The second category, intra-field overlay error, is the positional offset of an individual point inside a field referenced to the nominal center of an individual exposure field. Intra-field overlay errors are generally composed of lens aberrations or distortions, scanning irregularities, and reticle alignment.
It is important for this discussion to realize that most overlay measurements are made on silicon product wafers after each photolithographic process, prior to final etch. Product wafers cannot be etched until the photoresist target patterns are properly aligned to the underlying target patterns. See Super Sparse Overlay Sampling Plans: An Evaluation of Methods and Algorithms for Optimizing Overlay Quality Control and Metrology Tool Throughput, J. Pellegrini, SPIE Vol. 3677, 72:82. Manufacturing facilities rely heavily on exposure tool alignment and calibration procedures to help insure that the scanner tools are aligning properly. See Stepper Matching for Optimum Line Performance, T. Dooly et al., SPIE Vol. 3051, 426:432, 1997; Mix-and-Match: A Necessary Choice, R. DeJule, Semiconductor International, 66:76, February 2000; Matching Performance for Multiple Wafer Steppers Using an Advanced Metrology Procedure, M. Van den Brink, et al., SPIE Vol. 921, 180:197, 1988. Inaccurate overlay modeling algorithms can corrupt the exposure tool calibration procedures and degrade the alignment accuracy of the exposure tool system. See Super Sparse Overlay Sampling Plans: An Evaluation of Methods and Algorithms for Optimizing Overlay Quality Control and Metrology Tool Throughput, supra.
Over the past 30 years the microelectronics industry has experienced dramatic rapid decreases in critical dimension by constantly improving photolithographic imaging systems. Today, these photolithographic systems are pushed to performance limits. As the critical dimensions of semiconductor devices approach 50 nm the overlay error requirements will soon approach atomic dimensions. See Life Beyond Mix-and-Match: Controlling Sub-0.18 Micron Overlay Errors, T. Zavecz, Semiconductor International, July 2000. To meet the needs of next generation device specifications new overlay methodologies will need to be developed. In particular, overlay methodologies that can accurately separate out systematic and random effects and break them into assignable causes will greatly improve device process yields. See A New Approach to Correlating Overlay and Yield, supra. In particular, those new overlay methodologies that can be implemented into advanced process control or automated control loops will be most important. See Comparisons of Six Different Intra-Field Control Paradigms in an Advanced Mix and Match Environment, J. Pellegrini, SPIE Vol. 3050, 398:406, 1997; Characterizing Overlay Registration of Concentric 5X and 1X Stepper Exposure Fields Using Inter-Field Data, F. Goodwin et al., SPIE Vol. 3050, 407:417, 1997. Finally, another area where quantifying lens distortion error is of vital concern is in the production of photo masks or reticles during the electron beam manufacturing process. See Handbook of Microlithography and Microfabrication, P. Rai-Choudhury, Vol. 1, 417 1997.
Semiconductor manufacturing facilities use some version of the following complex overlay procedure to help determine the magnitude of intra-field distortion independent of other sources of systematic overlay error—in fact, the technique is used for both photolithographic steppers and scanners. The technique has been simplified for illustration. See Analysis of Image Field Placement Deviations of a 5× Microlithographic Reduction Lens, D. MacMillen et al., SPIE Vol. 334, 78:89, 1982. FIG. 33 shows a typical overlay target—one large or outer box and one small or inner target box. FIG. 31 shows a typical portion of a distortion test reticle used in the prior art. It should be noted that the chrome target patterns on most reticles are 4 or 5 times larger as compared with the patterns they produce at the image plane, this simply means modern step and scan systems (scanners) are reduction imaging systems. Further, for purposes of discussion, it is assumed that the reticle pattern is geometrically perfect, (in practice, the absolute positions of features on the reticle can be measured and the resulting errors subtracted off). First, a wafer covered with photoresist is loaded onto the wafer stage and globally aligned. Next, the full-field image of the reticle, see FIG. 2, is exposed onto the photoresist-coated wafer. See FIGS. 31 and 32. For purposes of illustration, it is assumed that the distortion test reticle consists of a 5×5 array of outer boxes evenly spaced a distance M*P, across the reticle surface, see FIG. 2. It is typically assumed that the center of the optical system is virtually aberration free. See Analysis of Image Field Placement Deviations of a 5× Microlithographic Reduction Lens, supra. With this assumption, the reticle, shown in FIG. 2 is now partially covered using the virtual reticle blades, as shown in FIG. 18, in such a way that only a single target at the center of the reticle field, box A in FIG. 2, is available for exposure. Next, the wafer stage is moved in such a way as to align the center of the reticle pattern directly over the upper left hand corner of the printed 5×5 outer box array, wafer position 1 in FIG. 31. The scanner then exposes the image of the small target box onto the photoresist coated wafer. If the wafer stage, optical system and scanning dynamics were truly perfect then the image of the small target box would fit perfectly inside the image of the larger target box, see FIG. 33, from the previous exposure. At this point the scanner and wafer stage are programmed to step and expose the small target box in the 5×5 array where each exposure is separated from the previous one by the stepping distance P.
With the assumption of a perfect stage, the final coordinates of the small target boxes are assumed to form a perfect grid, where the spacing of the grid is equal to the programmed stepping distance, P. Finally, if the first full-field exposure truly formed a perfect image, then the entire 5×5 array of smaller target boxes would fit perfectly inside the 5×5 array of larger target boxes. Since the first full-field exposure pattern is in fact distorted due to an imperfect imaging system (and scanner system) the actual position of the larger target box will be displaced relative to the smaller target boxes. The wafer is then sent through the final few steps of the lithographic process to create the final photoresist patterned overlay targets.
The resulting overlay error at each field position can be measured with a standard optical overlay tool and the result is interpreted as being intra-field error. Using the models described below in Equations 1 and 2, the overlay data can be analyzed and the lens distortion error is calculated.
The following intra-field modeling equations are commonly used to fit the overlay data using a least square regression technique. See Analysis of Image Field Placement Deviations of a 5× Microlithographic Reduction Lens, supra; Super Sparse Overlay Sampling Plans: An Evaluation of Methods and Algorithms for Optimizing Overlay Quality Control and Metrology Tool Throughput, supra.dxf(xf,yf)=Tx+s*xf−q*yf+t1*xf2+t2*xf*yf−E*(xf3+xf*yf2)  Equation 1dyf(xf,yf)=Ty+s*yf+q*xf+t2*yf2+t1*xf*yf−E*(yf3+yf*xf2)  Equation 2where;    (xf,yf)=intra-field coordinates    (dxf, dyf)(xf,yf)=intra-field distortion at position (xf,yf)    (Tx, Ty)=(x,y) intra-field translation    s=intra-field overall scale or magnification    q=intra-field rotation    (t1, t2)=intra-field trapezoid error    E=intra-field lens distortion.
A problem with this technique is two-fold, first, it is standard practice to assume that the wafer stage error is very small, randomly distributed, and can be completely accounted for using a statistical model. See Analysis of Image Field Placement Deviations of a 5× Microlithographic Reduction Lens, supra; A “Golden Standard” Wafer Design for Optical Stepper Characterization”, K. Kenp et al., SPIE Vol. 1464, 260:266, 1991; Matching Management of Multiple Wafer Steppers Using a Stable Standard and a Matching Simulator, M. Van den Brink et al., SPIE Vol. 1087, 218:232, 1989; Matching Performance for Multiple Wafer Steppers Using an Advanced Metrology Procedure, supra. In general, positional uncertainties in the wafer stage introduces both systematic and random errors, and since the intra-field distortion is measured only in reference to the lithography tool's wafer stage, machine to machine wafer stage differences show up as inaccurate intra-field distortion maps. Secondly, the assumption that lens distortion is zero at the center of the lens is incorrect. Furthermore, the model represented by Equations 1 and 2 is entirely unsuited to modeling scanner overlay error—typically the intra-field distortion model accounts only for scanner skew and scanner scale overlay errors—in general, the synchronization errors between the reticle stage and wafer stage introduce more complex errors described below.
A technique for stage and ‘artifact’ self-calibration is described in See Self-Calibration in two-Dimensions: The Experiment, M. Takac et al., SPIE Vol. 2725, 130:146, 1996; Error Estimation for Lattice Methods of Stage Self-Calibration, M. Raugh, SPIE Vol. 3050, 614:625, 1997. It consists of placing a plate (artifact) with a rectangular array of measurable targets on a stage and measuring the absolute positions of the targets using a tool stage and the tool's image acquisition or alignment system. This measurement process is repeated by reinserting the artifact on the stage but shifted by one target spacing in the X-direction, then repeated again with the artifact inserted on the stage shifted by one target spacing in the Y-direction. Finally, the artifact is inserted at 90-degrees relative to its initial orientation and the target positions measured. The resulting tool measurements are a set of (x, y) absolute positions in the tool's nominal coordinate system. Then, the absolute positions of both targets on the artifact and a mixture of the repeatable and non-repeatable parts of the stage x, y grid error are then determined to within a global translation (Txg, Tyg), rotation (qg) and overall scale ((sxg+syg)/2) factor.
This technique has several drawbacks, including that it requires that the measurements be performed on the same machine that is being assessed by this technique. Furthermore, this technique requires measurements made on a tool in absolute coordinates; the metrology tool measures the absolute position of the printed targets relative to its own nominal center; so absolute measurements are required over the entire imaging field, with a typical size greater than about 100 mm2).
Another technique for the determination of intra-field distortion is the method of Smith, McArthur, and Hunter (“Method And Apparatus For Self-Referenced Projection Lens Distortion Mapping”, U.S. patent application Ser. No. 09/835,201, now U.S. Pat. No. 6,573,986). It is a self-referencing technique that can be utilized with overlay metrology tools in a production environment. For diagnosing the intra-field scanner distortion in the presence of significant scanner non-repeatability, this technique teaches the use of a special reticle that has reduced optical transmission that is multiply scanned producing sub-Eo exposures on the wafer. The result is that this technique can be used to accurately determine the repeatable part of the scanner intra-field distortion but not that part of the intra-field distortion that changes from scan to scan, a simple example of which is the scanner y-magnification.
Another drawback to these techniques to determine intra-field error is that they use the scanner itself as the metrology tool. Due to the cost of scanners, which can exceed 10 million dollars, it is desirable to have a technique for intra-field error that does not use the scanner itself as the metrology tool for determining intra-field distortion but utilizes relatively inexpensive overlay metrology tools. Furthermore, it is desirable that the technique be easy to perform thereby allowing it to be used in a production environment by the day-to-day operating personnel. It is further desirable to have a technique that measures the non-repeatable parts of the scanner intra-field distortion.
Therefore there is a need for an effective, and efficient, way to determine the scanner intra-field error.